This TB Hackday script uses (pre-processed) RNA sequencing data from the following study to identify granuloma-associated T cell genes:
Then the expression of these genes can be further examined and validated using pseudo-bulk transcriptomic data from scRNAseq data in this study:
Foreman et al. compared the gene expression of T cells isolated from PBMC vs. T cells from granulomas (n=4 NHP, n=23 granulomas). They identified genes that were associated with granuloma T cells, and specifically identified genes that were correlated with Mtb burden in the granuloma (CFU).
Foreman et al. 2023 Granuloma-associated T cell genes
Bromley et al. report on an experiment with three groups of
cynomolgus macaques: (1) anti-CD4 treated, Mtb-exposed (n=7), (2) IgG
control, Mtb-exposed (n=6), (3) No treatment, Mtb-naive (n=6). Groups
(2) and (3) were infected with Mtb, then given an anti-CD4 antibody to
deplete CD4+ T cells or an isotype control (IgG) antibody, and finally
challenged with a secondary Mtb infection. Group 3 only received a
primary Mtb infection. Granulomas were then analyzed using single-cell
RNAseq, with 3 NHP from (1) and 2 NHP from (2) and (3) each. We have
created pseudo-bulk datasets using two different clustering of the
cells, offering two levels of cell type granularity for analysis:
bromley_X_pseudobulk_counts.csv where X is
coarse or subclustering, with clusters defined
by the authors of the manuscript. By analyzing data from primary
infection, reinfection, and reinfection-CD4+ T cell-depleted granulomas,
they found that the presence of CD4+ T cells during reinfection resulted
in a less inflammatory lung milieu characterized by reprogrammed CD8+ T
cells, reduced neutrophilia, and blunted type 1 immune signaling among
myeloid cells.